Hire the Best Hadoop Developers & Programmers

I'm a dynamic data expert with a proven ability to deliver short- and long-term projects in the realms of data engineering, data warehousing, and business intelligence. My passion is to partner with my clients to deliver top-notch, scalable data solutions to provide immediate and lasting value. I specialise in the following data solutions: ✔️ Data strategy advisory & technology selection/recommendation ✔️ Building data warehouses using modern cloud platforms and technologies ✔️ Creating and automating data pipelines, real-time streaming & ETL processes ✔️ Data Cleaning and Processing. ✔️ Data Migration (Heterogeneous and Homogeneous) Some of the technologies I most frequently work with are: ☁️ Cloud: GCP, AWS & Azure 👨‍💻 Databases: BigQuery, Google Cloud SQL, SQL Server, Snowflake, PostgreSQL, MySQL, S3, Google Cloud Storage, Azure Data Lake Storage. ⚙️ Data Integration/ETL: Matillion ETL for Snowflake/BigQuery, Apache Airflow( Google Cloud Composer, AWS MWAA, Astronomer), Azure Data Factory, Azure Logic Apps, Dagster and DBT. 🔑 Scripting - Python for API Integrations and Data Processing. 🤖 Serverless Solutions - Google Cloud Functions, Lambda Functions and Azure Functions. 📊 Dashboard Reporting - Microsoft Power BI, Apache Superset, Metabase, Looker Studio and Plotly. 🛠 Others - Process Automation in Python, N8N and Much More. =What my clients say about me== ------------------------------------------------------ "Waqar is very clued up, and he thinks outside the box. He is always looking for ways to implement the solution efficiently and cost-effectively. His communication skills are excellent. He is willing to go the extra mile. He has been a pleasure to work with. I will be working with him in the future." ⭐⭐⭐⭐⭐ ------------------------------------------------------ "Waqar has expert-level knowledge of Google Cloud and knows how to make cloud technologies work effectively for the marketing domain." ⭐⭐⭐⭐⭐ ------------------------------------------------------ I am highly attentive to detail, organised, efficient, and responsive. Let's get to work! 💪

With over 15 years of diverse industry experience, I bring a strong track record in building and optimizing data-intensive systems. For the past decade, I’ve specialized in Big Data technologies, including Hadoop and Spark, where I’ve designed and implemented scalable data pipelines capable of processing petabyte-scale datasets. My work has consistently focused on performance tuning and cost optimization—achieving infrastructure cost reductions of up to 80% through advanced Spark job tuning and architectural improvements. Earlier in my career, I gained hands-on experience in developing Python-based scrapers, automation scripts, and RESTful APIs, and I also built native iOS applications using Objective-C. This breadth of experience has given me a solid foundation across the full technology stack. I’ve led the development of data lakes for leading e-commerce and fintech companies, enabling robust data infrastructure for analytics and machine learning. Having worked at multiple startups, I thrive in dynamic environments and adapt quickly to various methodologies, including Agile and Kanban.

Your data pipeline is either driving decisions, or quietly slowing your business down. Most teams don’t struggle with data volume, they struggle with reliability. Pipelines fail without alerts, dashboards lag behind reality, and engineers spend more time fixing than building. The result is slower decisions, growing technical debt, and missed opportunities. I design and build robust, scalable data systems that simply work, from ingestion to analytics-ready data. The focus is always on clarity, performance, and reliability, so your team can trust the data and move faster without constant firefighting. My tech stack: Python, SQL, Spark, Apache NiFi, Airflow, Kafka, Flink, Snowflake, BigQuery, AWS, GCP, Docker, Terraform, and FastAPI. If you share your current setup or challenge, I’ll break down exactly how to fix or scale it. I usually respond within a few hours.

Staff Engineer at Samsung Research with 12+ years building large-scale data platforms. I specialize in end-to-end data infrastructure — from real-time streaming pipelines (Kafka, Kinesis) to batch processing (Apache Spark, Airflow/Cloud Composer) to modern lakehouse architectures (Apache Iceberg, StarRocks, Trino, BigQuery). What I bring to your project: • Spark internals & performance tuning (Catalyst optimizer, Tungsten, AQE, shuffle optimization) • Lakehouse design on GCP/AWS — Iceberg, Delta Lake, BigQuery, Dataproc • Real-time pipelines with Kafka, Kinesis, and Structured Streaming • Cloud infrastructure — AWS Solutions Architect Professional certified, GCP certified • Kubernetes-native deployments (CKD certified) MTech in Big Data Engineering from BITS Pilani. I work with precision, deliver documentation with every engagement, and communicate clearly throughout. Available for architecture consulting, pipeline audits, Spark performance tuning, and data engineering mentorship.

I'm a Senior Data Engineer with 8+ years of strong technical expertise in building reliable and scalable data infrastructure, from data ingestion to transformation to warehousing, streaming, and data analytics, specializing in dbt, Snowflake, Airflow, Databricks (and more) across AWS, Azure, and GCP, with robust ELT and ETL pipelines. If your data pipelines are brittle, your data warehouse is slow, or your data was never built to scale, that is exactly what I fix, with fault tolerance, observability, and audit-ready quality engineered in from day one. I cover the full data engineering lifecycle: batch and real-time data pipelines, Modern Data Stack builds, lakehouse architecture, cloud and warehouse data migration, governance, and the data foundations that feed modern systems. 🎯 Core Expertise: ✅ Data Pipelines & Orchestration: End-to-end batch and real-time pipelines with Apache Airflow, Dagster, Prefect, AWS Step Functions, and Azure Data Factory. Idempotent, schema-drift tolerant, and monitored so failures surface before they reach your stakeholders. ✅ Cloud Warehousing & Lakehouse: Snowflake, BigQuery, Amazon Redshift, Databricks, and Microsoft Fabric, with Delta Lake and Apache Iceberg lakehouse foundations governed through the Glue Data Catalog and Lake Formation, with Athena and Redshift Spectrum for serverless queries, Medallion Architecture, partitioning, and performance tuning. ✅ Data Transformation & Modeling: dbt (Core and Cloud), SQLMesh, Spark and PySpark on EMR and AWS Glue, Star Schema and dimensional modeling, analytics engineering best practices, full test coverage, and CI/CD for data models. ✅ Streaming & Real-Time Analytics: Distributed streaming with Apache Kafka, Flink, Spark Structured Streaming, Kinesis, and Pub/Sub, including exactly-once semantics, dead-letter queues, CDC, and end-to-end latency guarantees. ✅ Data Ingestion & Integration: Fivetran, Airbyte, Matillion, Stitch, Hevo, Meltano, and custom CDC pipelines for near-real-time sync across structured, semi-structured, and unstructured sources. ✅ Data Quality, Governance & Observability: Automated data quality frameworks, SLA monitoring, auditable lineage, data catalog and metadata management, and observability that catches bad data early. ✅ Cloud Migration & Modernization: Zero-downtime migration handled end to end, from legacy warehouse assessment through cutover, with zero data loss and minimal downtime, replacing brittle ETL and ELT with a clean Modern Data Stack. ✅ AI-Ready Data Infrastructure: Pipelines engineered to feed LLMs and ML systems with clean, structured, high-quality data, from ingestion through transformation to serving. ------------------------------------------------------ ⚙️Tech Stack: ⚡ Warehouses & Lakehouse: Snowflake | BigQuery | Redshift | Databricks | Microsoft Fabric | Athena | Delta Lake | Iceberg ⚡ Transformation: dbt | SQLMesh | Spark | PySpark | AWS Glue | EMR | Star Schema | Medallion Architecture ⚡ Orchestration: Airflow (GCP Cloud Composer and AWS MWAA) | Dagster | Prefect | Azure Data Factory | Step Functions ⚡ Streaming: Kafka | Flink | Kinesis | Pub/Sub | Spark Structured Streaming | ClickHouse ⚡ Ingestion: Fivetran | Airbyte | Matillion | Stitch | Hevo | Meltano | CDC ⚡ Governance & Catalog: Glue Data Catalog | Lake Formation | Unity Catalog | Microsoft Purview | Dataplex ⚡ Cloud: AWS | GCP | Azure ⚡ Languages: Python | SQL (Snowflake, BigQuery, T-SQL, PL/pgSQL) | FastAPI ⚡ Databases: PostgreSQL | MySQL | SQL Server | DynamoDB | MongoDB ⚡ BI & Reporting: Looker | Tableau | Power BI | GA4 | Metabase | Superset | Streamlit | Grafana ------------------------------------------------------ ⭐ What Clients Say: 🏅 "Adarsh rebuilt our analytics pipeline on Snowflake, Airflow, and dbt, giving us reliable, version-ready data. Reporting accuracy improved overnight, and we can finally trust the numbers." – Anita, Head of Product, FinTech SaaS 🏅 "He designed a zero-downtime migration to a modern data warehouse that cut query latency by more than half while keeping our SLAs intact." – Daniel, VP of Data, AdTech Firm 🏅 "Clean architecture, solid dbt models, and Airflow pipelines running without issues for months. He brought a level of engineering discipline we hadn't seen from a data consultant before." – Mark, Director of Data Engineering, E-commerce Startup 🏅 "We came to him with a Spark pipeline costing us a fortune and delivering stale data. He restructured the workflow logic and cut processing time by 70%." – Leo, Head of Analytics, HealthTech SaaS ------------------------------------------------------ 🏆 TOP RATED PLUS | EXPERT-VETTED | Top 1% on Upwork | 8+ Years Experience | 100% Job Success 🚀 Ready to build a scalable, production-ready data infrastructure to turn your raw data into reliable, actionable business insights? Click the 'Invite to Job' button on the top right, and let's discuss your data pipeline!

Struggling to unlock value from your data or build scalable, high-performance analytics platforms? I’m 𝑯𝒂𝒔𝒆𝒆𝒃 𝑨𝒔𝒊𝒇,a Senior Data Engineer specializing in Databricks, Snowflake, Big Data Engineering, and scalable ETL/ELT solutions. With expertise in PySpark, Python, SQL, GCP, AWS, Azure, and NLP, I build high-performance data pipelines, cloud data platforms, and real-time analytics solutions. Experienced in data warehousing, cloud integration, machine learning workflows, and performance optimization to transform raw data into actionable business insights. Let’s build reliable, scalable, and data-driven solutions for your business growth. I’ve successfully completed 99+ projects across industries, designing ETL pipelines, MLOps workflows, Delta Lake architectures, and cloud analytics solutions on AWS, Azure, and GCP. ✔️ 𝑯𝒐𝒘 𝑰 𝑯𝒆𝒍𝒑 𝑩𝒖𝒔𝒊𝒏𝒆𝒔𝒔𝒆𝒔 𝑻𝒓𝒂𝒏𝒔𝒇𝒐𝒓𝒎 𝑫𝒂𝒕𝒂 𝒊𝒏𝒕𝒐 𝑰𝒏𝒔𝒊𝒈𝒉𝒕𝒔 ➜ Databricks & Big Data Engineering I specialize in designing enterprise-grade Databricks Lakehouse architectures and Delta Lake solutions. My expertise in Spark and PySpark allows me to build high-performance pipelines for both batch and real-time analytics, ensuring your data infrastructure is robust and scalable. ➜ Machine Learning & MLOps With a focus on machine learning and MLOps, I build and deploy predictive models using tools like MLflow and TensorFlow. I automate end-to-end ML pipelines to enhance efficiency and accuracy, driving impactful insights from your data. ➜ Cloud & Data Platforms I implement secure, scalable cloud solutions on platforms like AWS, Azure, and GCP. My experience includes cloud migration, Kubernetes, Docker, and CI/CD automation, ensuring seamless integration and optimal performance. ➜ ETL & Data Pipelines I develop reliable ETL processes and data pipelines that streamline data integration and transformation. My work with streaming analytics using Kafka and Spark ensures real-time data processing and actionable insights. ➜ Data Analyst & Visualization I create actionable dashboards and visualizations using Power BI, Tableau, and Databricks SQL. My focus is on driving KPI reporting and business intelligence to support strategic decision-making. ➜ Snowflake I leverage Snowflake's capabilities to build efficient data warehousing solutions, optimizing data storage and retrieval for enhanced performance and scalability. ➜ Python My proficiency in Python allows me to develop complex data processing scripts and machine learning models, ensuring robust and efficient data handling. ➜ NLP (Natural Language Processing) I apply NLP techniques to extract meaningful insights from unstructured data, enabling advanced text analytics and improved decision-making processes. ➜ GCP (Google Cloud Platform) I utilize GCP's powerful tools to design and deploy scalable cloud solutions, ensuring high availability and performance for your data-driven applications. ➜ Data Warehouses I design and manage data warehouses that provide a centralized repository for your data, facilitating efficient data analysis and reporting. ✔️ 𝑲𝒆𝒚 𝑻𝒐𝒐𝒍𝒔 & 𝑻𝒆𝒄𝒉𝒏𝒐𝒍𝒐𝒈𝒊𝒆𝒔 ▪ Databricks & Big Data: Databricks, Delta Lake, Apache Spark, PySpark, Unity Catalog, Kafka, Hadoop, Real-time Streaming ▪ Machine Learning: MLflow, TensorFlow, PyTorch, scikit-learn, Feature Store, Predictive Analytics, NLP ▪ Cloud Platforms: AWS, Azure, GCP, Kubernetes, Docker, CI/CD ▪ Analytics & BI: Power BI, Tableau, Databricks SQL, KPI Dashboards, Data Strategy ▪ Data Engineering: ETL Pipelines, Data Lakes, Data Warehousing, Data Migration, Performance Optimization ✔️ 𝑾𝒉𝒚 𝑪𝒉𝒐𝒐𝒔𝒆 𝑴𝒆 I combine deep technical expertise with practical business understanding, delivering scalable, cost-efficient, and AI-ready data solutions. My goal is to turn your data into a strategic asset that powers smarter decisions and measurable growth. Let’s collaborate to build your next-generation analytics platform and unlock the full potential of your data. Check my portfolio for architecture samples, dashboards, and case studies. Databricks Engineer, Big Data Consultant, Spark Developer, MLOps Engineer, Data Engineer, AWS Data Specialist, Azure Databricks, GCP Analytics, ETL Developer, Data Analytics, Delta Lake Expert, Machine Learning Engineer, Python, Database Architecture, Data Processing, ETL, Big Data, Database Design, Data Engineering, Data Analytics & Visualization Software, Data Visualization, Deep Learning Modeling, Data Warehousing & ETL Software, Snowflake, Amazon Web Services, ETL Pipeline, Machine Learning, Deep Learning, Data Science, Data Analysis, Cloud Engineering, Artificial Intelligence, Databricks Engineer, Big Data Consultant, Spark Developer, MLOps Engineer, Data Engineer, AWS Data Specialist, Senior Data Engineer specializing in Databricks, Snowflake, Big Data Engineering, and scalable ETL/ELT solutions. With expertise in PySpark, Python, SQL, GCP, AWS, Azure, and NLP